Perceptual Evaluation of Signal-to-Noise-Ratio-Aware Dynamic Range Compression in Hearing Aids

Kowalewski, Borys; Dau, Torsten; May, Tim

doi:10.1177/2331216520930531

Cited by 7 publications

(3 citation statements)

References 67 publications

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“…Hassager et al (2017) used a single-microphone classification method to separate direct from reverberant signal components, helping to preserve spatial cues that can be distorted by DRC. May et al (2018) proposed a single-microphone separation system that applies fast-acting compression to speech components and slow-acting compression to noise components; listening experiments with an oracle separation algorithm improved both quality and intelligibility (Kowalewski et al, 2020). Corey and Singer (2017) used a multimicrophone separation method to apply separate compression functions to each of several competing speech signals.…”

Section: Discussionmentioning

confidence: 99%

Modeling the effects of dynamic range compression on signals in noise

Corey,

Singer

2020

Preprint

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Hearing aids use dynamic range compression (DRC), a form of automatic gain control, to make quiet sounds louder and loud sounds quieter. Compression can improve listening comfort, but it can also cause distortion in noisy environments. It has been widely reported that DRC performs poorly in noise, but there has been little mathematical analysis of these distortion effects. This work introduces a mathematical model to study the behavior of DRC in noise. Using statistical assumptions about the signal envelopes, we define an effective compression function that models the compression applied to one signal in the presence of another. This framework is used to prove results about DRC that have been previously observed experimentally: that when DRC is applied to a mixture of signals, uncorrelated signal envelopes become negatively correlated; that the effective compression applied to each sound in a mixture is weaker than it would have been for the signal alone; and that compression can reduce the long-term signal-to-noise ratio in certain conditions. These theoretical results are supported by software experiments using recorded speech signals.

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Section: Discussionmentioning

confidence: 99%

Modeling the effects of dynamic range compression on signals in noise

Corey,

Singer

2020

Preprint

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“…Similarly, other studies have shown that improved audibility of speech in quiet has been associated with improved speech recognition with FAST WDRC, compared to linear amplification (Souza & Turner 1998, 1999 or SLOW WDRC (Kowalewski et al 2018). More generally, there is evidence suggesting that distortion from FAST WDRC may be reduced if some form of processing is applied to effectively decouple the target speech from the background noise (May et al 2018;Kowalewski et al 2020) or reverberation (Hassager et al 2017a(Hassager et al , 2017b prior to compression. Thus, the pattern of effects reported by Wu and Stangl combined with studies showing the improved audibility or reduced distortion with FAST WDRC on speech in quiet suggest that hearing aid directionality settings may impact outcomes with WDRC-related signal modification.…”

Section: Wdrc and Directionalitymentioning

confidence: 99%

Effects of Directionality, Compression, and Working Memory on Speech Recognition

2020

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Objectives: Previous research has shown that the association between hearing aid processed speech recognition and individual working memory ability becomes stronger in more challenging conditions (e.g., higher background noise levels) and with stronger hearing aid processing (e.g., fast-acting wide dynamic range compression, WDRC). To date, studies have assumed omnidirectional microphone settings and collocated speech and noise conditions to study such relationships. Such conditions fail to recognize that most hearing aids are fit with directional processing that may improve the signal-to-noise ratio (SNR) and speech recognition in spatiallyseparated speech and noise conditions. Here, we considered the possibility that directional processing may reduce the signal distortion arising from fast-acting WDRC and in turn influence the relationship between working memory ability and speech recognition with WDRC-processing. The combined effects of hearing aid processing (WDRC and directionality) and SNR were quantified using a signal modification metric (cepstral correlation) which measures temporal envelope changes in the processed signal with respect to a linearly amplified reference. It was hypothesized that there will be a weaker association between working memory ability and speech recognition for hearing aid processing conditions that result in overall less signal modification (i.e., fewer changes to the processed envelope).Design: Twenty-three hearing-impaired individuals with bilateral, mild to moderately-severe sensorineural hearing loss participated in the study. Participants were fit with a commercially available hearing aid and signal processing was varied in two dimensions: i) Directionality (omnidirectional [OMNI] versus fixed-directional [DIR]), and ii) WDRC speed (fast-acting [FAST] versus slow-acting [SLOW]). Sentence recognition in spatially-separated multi-talker babble was measured across a range of SNRs: 0 dB, 5 dB, 10 dB, and quiet. Cumulative signal modification was measured with individualized hearing aid settings, for all experimental conditions. A linear mixed-effects model was used to determine the relationship between speech recognition, working memory ability, and cumulative signal modification.Results: Signal modification results showed a complex relationship between directionality and WDRC speed, that varied by SNR.

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“…Listening tests have shown that combining source separation and WDRC can reduce noise “annoyance” but does not improve speech intelligibility compared to a system with linear gain ( Brons et al, 2015 ; Kortlang et al, 2018 ). Listening tests with an adaptive compression system have demonstrated preserved spatial cues in reverberant environments ( Hassager et al, 2017 ), as well as increased speech intelligibility and increased subjective preference compared to conventional compression systems ( Kowalewski et al, 2020 ). However, the adaptive compression system has only been evaluated in either noisy or reverberant conditions, but not in realistic conditions with both interfering noise and room reverberation.…”

Section: Introductionmentioning

confidence: 99%

A Data-driven Distance Metric for Evaluating the effects of Dynamic Range Compression in Adverse Conditions

Overby,

Dau,

May

2023

Trends in Hearing

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Dynamic range compression is a crucial component in hearing aids, aiming to restore audibility for hearing-impaired listeners. However, determining suitable compression parameters, such as the time constants for the level estimation stage, remains a topic of debate, as the perceptual benefit of different parameter configurations varies depending on the acoustic conditions. In this study, a data-driven distance metric based on physical metrics was developed to evaluate and compare the performance of various compression systems. This analysis encompassed fast-acting and slow-acting compression, as well as a “scene-aware” compression that dynamically adjusted the release time constant based on the presence of the target. A reference system called “source-independent compression” was also considered, which had access to individual speech and noise signals. Multiple physical metrics were employed to assess the effects of these different compression systems under diverse acoustic conditions, including varying levels of interfering noise and degrees of room reverberation. Factor analysis was applied to derive a concise set of interpretable features representing the impact of compression, expressed as linear combinations of carefully selected objective metrics. The reduced dimensional representation enabled the use of the Manhattan distance to measure the similarity between the compression systems. Results demonstrated that the scene-aware compressor generally exhibited a smaller distance to the reference system compared to both the fast-acting and slow-acting compressors. This finding suggests that an adaptive compression system holds potential benefits across a range of acoustic conditions.

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Perceptual Evaluation of Signal-to-Noise-Ratio-Aware Dynamic Range Compression in Hearing Aids

Cited by 7 publications

References 67 publications

Modeling the effects of dynamic range compression on signals in noise

Modeling the effects of dynamic range compression on signals in noise

Effects of Directionality, Compression, and Working Memory on Speech Recognition

A Data-driven Distance Metric for Evaluating the effects of Dynamic Range Compression in Adverse Conditions

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